Biology subjects

Blanco, R.

Publications and source records attributed to Blanco, R..

9 recordsLinked to original sources

bioRxiv2026

Linking Infection, Immunity, and Symptoms for Age-Dependent Influenza Severity

Influenza infection results from tightly coupled interactions between viral replication, host immune responses, and the emergence of clinical symptoms. While mathematical models have extensively characterized viral and immune dynamics, the mechanistic link between immune activity and disease severity remains poorly understood. Here, we develop an integrative, within-host modeling framework that explicitly connects infection dynamics, immune responses, and symptom manifestation through a unified dynamical system. Using murine influenza data, we incorporate key immune components alongside a mechanistic representation of symptom progression, quantified via host weight loss.Our analysis identifies inflammatory signaling, particularly TNF- mediated pathways, as a central driver linking immune activity to symptom severity. Importantly, we demonstrate that age-dependent alterations in immune regulation reshape this coupling: aged hosts exhibit prolonged inflammatory responses that amplify and sustain symptom burden despite comparable viral kinetics. These results highlight that disease severity cannot be inferred from viral load alone, but instead emerges from the dynamical interplay between immune regulation and host physiology. This framework provides a quantitative basis for understanding age-specific morbidity and offers a foundation for designing interventions that target immune-mediated pathology rather than viral replication alone.

systems biology↗

bioRxiv2025

Computational Platform for streamlining the success of sequential antibiotic therapy

The scarcity of antibiotics and the need for swift decision-making present significant challenges for healthcare practitioners. When confronted with such circumstances, practitioners must prioritize their approach based on several key factors. By leveraging the recent biological discovery of collateral sensitivity, we have devised an open-source computational platform. This platform utilizes the drug resistance profile of an evolved strain and initial population conditions to potentially predict the failure of cycling therapy in eradicating or restraining a multi-drug resistant bacterial population. We demonstrate how this framework can anticipate potential failures for a range of antibiotics in chronic pseudomonas aeruginosa infections. This innovative methodology lays the foundation for evolutionary therapies that can facilitate the selection of appropriate treatments, thereby reducing antibiotic resistance.

evolutionary biology↗

bioRxiv2024

Structure-Function Relationship in Electrical and Hemodynamic Brain Networks: Insights from EEG and fNIRS during Rest and Task States

Identifying relationships between structural and functional networks is crucial for understanding the large-scale organization of the human brain. The potential contribution of emerging techniques like functional near-infrared spectroscopy to investigate the structure-functional relationship has yet to be explored. In our study, we characterize global and local structure-function coupling using source-reconstructed Electroencephalography (EEG) and Functional near-infrared spectroscopy (fNIRS) signals in both resting state and motor imagery tasks, as this relationship during task periods remains underexplored. Employing the mathematical framework of graph signal processing, we investigate how this relationship varies across electrical and hemodynamic networks and different brain states. Results show that fNIRS structure-function coupling resembles slower-frequency EEG coupling at rest, with variations across brain states and oscillations. Locally, the relationship is heterogeneous, with greater coupling in the sensory cortex and increased decoupling in the association cortex, following the unimodal to transmodal gradient. Discrepancies between EEG and fNIRS are noted, particularly in the frontoparietal network. Cross-band representations of neural activity revealed lower correspondence between electrical and hemodynamic activity in the transmodal cortex, irrespective of brain state while showing specificity for the somatomotor network during a motor imagery task. Overall, these findings initiate a multimodal comprehension of structure-function relationship and brain organization when using affordable functional brain imaging.

neuroscience↗

bioRxiv2023

Investigating the Interaction Between EEG and fNIRS: A Multimodal Network Analysis of Brain Connectivity

The brain is a complex system with functional and structural networks. Different neuroimaging methods have their strengths and limitations, depending on the signals they measure. Combining techniques like electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) techniques has gained interest, but understanding how the information derived from these modalities is related remains an exciting open question. Successful integration of these modalities requires a sophisticated mathematical framework that goes beyond simple comparative analyses. The multilayer network model has emerged as a promising approach. This study is an extended version of the conference paper "Resting State Brain Connectivity Analysis from EEG and FNIRS Signals" [5]. In this study, we explored the brain network properties obtained from EEG and fNIRS data using graph analysis. Additionally, we adopted the multilayer network model to evaluate the benefits of combining multiple modalities compared to using a single modality. A small-world network structure was observed in the rest, right motor imagery, and left motor imagery tasks in both modalities. We found that EEG captures faster changes in neural activity, thus providing a more precise estimation of the timing of information transfer between brain regions in RS. fNIRS provides insights into the slower hemodynamic responses associated with longer-lasting and sustained neural processes in cognitive tasks. The multilayer approach outperformed unimodal analyses, offering a richer understanding of brain function. Complementarity between EEG and fNIRS was observed, particularly during tasks, as well as a certain level of redundancy and complementarity between the multimodal and the unimodal approach, which is dependent on the modality and on the specific brain state. Overall, the results highlight differences in how EEG and fNIRS capture brain network topology in RS and tasks and emphasize the value of integrating multiple modalities for a comprehensive view of brain connectivity and function.

neuroscience↗

bioRxiv2023

Resting State Brain Connectivity analysis from EEG and FNIRS signals

Contemporary neuroscience is highly focused on the synergistic use of machine learning and network analysis. Indeed, network neuroscience analysis intensively capitalizes on clustering metrics and statistical tools. In this context, the integrated analysis of functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) provides complementary information about the electrical and hemodynamic activity of the brain. Evidence supports the mechanism of the neurovascular coupling mediates brain processing. However, it is not well understood how the specific patterns of neuronal activity are represented by these techniques. Here we have investigated the topological properties of functional networks of the resting-state brain between synchronous EEG and fNIRS connectomes, across frequency bands, using source space analysis, and through graph theoretical approaches. We observed that at global-level analysis small-world topology network features for both modalities. The edge-wise analysis pointed out increased inter-hemispheric connectivity for oxy-hemoglobin compared to EEG, with no differences across the frequency bands. Our results show that graph features extracted from fNIRS can reflect both shortand longrange organization of neural activity, and that is able to characterize the large-scale network in the resting state. Further development of integrated analyses of the two modalities is required to fully benefit from the added value of each modality. However, the present study highlights that multimodal source space analysis approaches can be adopted to study brain functioning in healthy resting states, thus serving as a foundation for future work during tasks and in pathology, with the possibility of obtaining novel comprehensive biomarkers for neurological diseases.

neuroscience↗

bioRxiv2022

MYC directly transactivates CR2/CD21, the receptor of the Epstein-Barr virus, and enhances the viral infection of Burkitt lymphoma cells

The molecular hallmark of Burkitt lymphoma (BL) is a chromosomal translocation that results in deregulated expression of MYC oncogene. This translocation is present in virtually all BL. MYC is an oncogenic transcription factor deregulated in about half of total human tumors, by translocation or other mechanisms. Transcriptomic studies reveal more than 1000 genes regulated by MYC but a much smaller fraction of these genes is directly activated by MYC. All the endemic BL and many sporadic BL cells are associated to the Epstein-Barr virus (EBV) infection. The currently accepted mechanism for the MYC and BL association is that EBV is the causing agent inducing MYC translocation. Complement receptor 2 or CR2 (also called CD21) is a membrane protein that serves as EBV receptor in lymphoid cells. Here we show that CR2 is a direct MYC target gene. This conclusion is based on several evidences. First, MYC downregulation is linked to CR2 downregulation both in proliferating and in arrested cells. Second, MYC binds human CR2 promoter and this binding depends on E-box elements. Third, MYC activates CR2 promoter in an E-box dependent manner. Four, MYC activates CR2 transcription in the absence of protein synthesis. Importantly, MYC also induces CR2 expression in mouse primary B cells. Thus, CR2 is a bona fide MYC direct target gene. Moreover, higher MYC expression levels in Burkitt lymphoma-derived cells result in a more efficient EBV infection. We propose an alternative mechanism compatible with the correlation between EBV infection and MYC translocation observed in endemic BL, i.e., that deregulated MYC in BL cells occurs first and favors the EBV infection.

cancer biology↗

bioRxiv2020

CCR5 deficiency impairs CD4+ T cell memory responses and antigenic sensitivity through increased ceramide synthesis

In CD4+ T cells, CCR5 is not only a coreceptor for HIV-1 infection, but also contributes to their functional fitness. Here we show that by limiting GATA-1-induced transcription of specific ceramide synthases, CCR5 signaling reduces ceramide levels and thereby increases T cell antigen receptor (TCR) nanoclustering in antigen-experienced mouse and human CD4+ T cells. This activity is CCR5-specific and independent of CCR5 costimulatory activity. CCR5-deficient mice showed reduced production of high affinity class-switched antibodies, but only after antigen rechallenge, which implies an impaired memory CD4+ T cell response. This study identifies a CCR5 function in the generation of CD4+ T cell memory responses, and establishes an antigen-independent mechanism that regulates TCR nanoclustering by altering specific lipid species.

immunology↗

bioRxiv2018

Myc stimulates cell cycle progression through the activation of Cdk1 and phosphorylation of p27

Cell cycle stimulation is a major transforming mechanism of Myc oncoprotein. This is achieved through at least three concomitant mechanisms: upregulation of cyclins and Cdks, downregulation of Cdk inhibitors p15 and p21 and the degradation of p27. The Myc-p27 antagonism has been shown to be relevant in human cancer. To be degraded, p27 must be phosphorylated at Thr-187 to be recognized by Skp2, a component of the ubiquitination complex. We previously described that Myc induces Skp2 expression. Here we show that not only Cdk2 but Cdk1 phosphorylates p27 at the Thr187, which was previously unreported. Moreover, Myc induced p27 degradation in murine fibroblasts through Cdk1 activation, which was achieved by Myc-dependent cyclin A and B induction. In the absence of Cdk2, p27 phosphorylation at Thr-187 was mainly carried out by cyclin A2-Cdk1 and cyclin B1-Cdk1. We also show that Cdk1 inhibition was sufficient for the synthetic lethal interaction with Myc. This result is relevant because Cdk1 is the only Cdk strictly required for cell cycle and the reported synthetic lethal interaction between Cdk1 and Myc.\n\nSummary blurbMyc antagonizes p27 activity in cancer. Myc activates Cdk1 to phosphorylate p27, marking p27 for degradation. This depends on Myc-mediated cyclin A and B induction. Cdk1 inhibition is sufficient for a synthetic lethal interaction with Myc

cancer biology↗

bioRxiv2017

The MYC antagonist MNT autoregulates its expression and supports proliferation in MAX deficient cells

MNT is a transcription factor of the MXD family. MNT-MAX dimers down-regulate genes by binding to E-box sequences, which can also be bound by MYC-MAX to activate transcription. MNT has been described as a modulator of MYC activity but little is known about MNT regulation and whether MNT has MAX-independent functions. Using a MAX deficient cell line and siRNA-mediated silencing of MAX, we show that in the absence of MAX, the total MNT levels are elevated and that MNT localizes both in the cytoplasm and the nucleus. In contrast, MNT is predominantly nuclear when MAX is expressed. MNT is required for optimal cell proliferation even in the absence of MAX, being the first report of a MAX-independent function of MNT. Interestingly, MNT forms homodimers and autoregulates its expression by repressing its own promoter. The tight MNT regulation and its activity in absence of MAX suggest its importance on cell homeostasis.

cancer biology↗